code: def numeric_score(prediction, groundtruth):
      """Computation of statistical numerical scores:
  
      * FP = False Positives
      * FN = False Negatives
      * TP = True Positives
      * TN = True Negatives
  
      return: tuple (FP, FN, TP, TN)
      """
      FP = np.float32(np.sum((prediction == 1) & (groundtruth == 0)))
      FN = np.float32(np.sum((prediction == 0) & (groundtruth == 1)))
      TP = np.float32(np.sum((prediction == 1) & (groundtruth == 1)))
      TN = np.float32(np.sum((prediction == 0) & (groundtruth == 0)))
      return FP, FN, TP, TN
  
file_path: medicaltorch/medicaltorch/metrics.py
imports: from collections import defaultdict
  from scipy import spatial
  import numpy
label_desc: Use image node_id 1 for calling a global function with example usage: numeric_score(prediction, groundtruth) and returns: FP,  FN,  TP,  TN